The association between metabolic parameters and evening chronotype and social jetlag in non-shift workers: A meta-analysis

Association Between Social Jetlag and Components of Metabolic Syndrome: A Systematic Review and Meta-Analysis

BACKGROUND

A mismatch between biological and social time, often referred to as social jetlag (SJL), can lead to inadequate sleep and activities or taking meals at times that do not align with our biological rhythms, increasing the risk of metabolic abnormalities. Although the association between sleep and metabolic syndrome (MetS) is well established, the effects of SJL on MetS and the components of MetS in adults remain unclear.

PURPOSE

This study was designed to explore the relationship between SJL and MetS components in adults.

METHODS

A systematic review and meta-analysis was conducted on studies registered in PubMed, Cochrane, Web of Science, and Embase between the inception of each database until November 15, 2023. We focused on studies designed to evaluate the relationship between SJL and either MetS or its components. Only studies using cross-sectional, prospective, or retrospective designs were considered for inclusion. The relationship between SJL and MetS was depicted as an odds ratio with a corresponding 95% confidence interval (CI). We determined the mean differences and 95% CIs to estimate the associations between SJL and MetS components. The Joanna Briggs Institute Critical Appraisal Checklist was used to evaluate the methodological rigor of the selected studies. Data were analyzed using RevMan software Version 5.4.

RESULTS

The systematic review included 16 studies, with five analyzed via a meta-analysis covering four outcomes, each based on two to three studies. When comparing SJL of less than 1 hour with SJL of 2 hours or more, the latter showed a higher likelihood of MetS (pooled odds ratio: 1.52). Although a significant decrease in systolic blood pressure (pooled mean differences = -3.52 mmHg, 95% CI [-6.41, -0.64]) and a significant increase in waist circumference (pooled mean differences = 2.17 cm, 95% CI [0.61, 3.73]) were observed, the correlation between SJL and diastolic blood pressure failed to reach statistical significance.

CONCLUSIONS/IMPLICATIONS FOR PRACTICE

The meta-analysis conducted in this study found an association between SJL and MetS. Healthcare practitioners should prioritize the management of sleep quality and duration, especially for individuals exhibiting substantial SJL. Improving sleep can aid in controlling blood pressure and managing weight and should form part of MetS management strategies.

Exploring the associations between chronotype, meal frequency, and physical activity: A population-based study in adults

Chronotype is an established concept designed to capture the internal clock's phase in real-life conditions. It is vital in many aspects of daily life and can interfere considerably with numerous factors in a given population. Recognizing nonmodifiable and modifiable factors is crucial for identifying covariates of interest when studying the link between chronotype and health status. To date, chronotype and its related factors have not been extensively investigated. The present study aimed to explore the association of chronotypes with meal frequency, physical activity, and demographic factors among the Saudi population. This cross-sectional web-based questionnaire involved 1369 adults (aged 18 years and above) from the general public in Saudi Arabia and was conducted between March and May 2019. Chronotype was assessed using the reduced version of the original Horne and Ostberg morningness-eveningness questionnaire (MEQ). Meal frequencies and demographics data (age, gender, marital status, place of residence, educational level, employment status, income) were obtained. Physical activity level was also obtained using the international physical activity questionnaire. The MEQ scores group individuals into three categories: morning-type, neither-type, and evening-type. The neither-type individuals represented 41.6% (95% confidence interval [CI], 37.5% - 45.6%) of the study population, followed by the morning-type (34.1%; 95% [CI], 29.8% - 38.4%), then the evening-type (24.3%, 95% [CI], 19.6% - 28.9%). Chronotype was significantly associated with age, marital status, employment status and monthly income (All p < 0.05). Significant associations between chronotype with meal frequencies (number of meals per day, breakfast frequency, lunch frequency, and dinner frequency) and physical activity were also observed (All p < 0.05). This study highlights that meal frequencies and physical activity levels are associated with chronotype distribution. Furthermore, demographics, including age, marital status, employment status, and income, were associated with chronotype distribution.

Relationship between social jetlag and body mass index in nurses working shift schedules: a cross-sectional study

This study aimed to explore the relationship between shift-working nurses' social jetlag and body mass index (BMI) and provide a theoretical basis for nursing managers to develop appropriate health interventions. Shift work is unavoidable in nursing and is associated with circadian rhythm disorders. Social jetlag is prevalent in shift-working nurses and is associated with adverse health outcomes (particularly metabolism-related indicators). BMI is a significant metabolic indicator, and research has demonstrated its effectiveness in predicting the formation of metabolic syndrome. The relationship between social jetlag and BMI can be explained by considering physiological, psychological, and behavioral factors. However, most studies on social jetlag and health status are focused on non-shift nurse populations, with fewer studies on shift workers. Five tertiary hospitals located at similar latitudes in Southwest China were selected for the study. We surveyed 429 shift-working nurses using sociodemographic data, the Munich Chronotype Questionnaire for Shift Workers, and BMI. The restricted cubic spline model was used to analyze the relationship between social jetlag and BMI among shift-working nurses, and segmented linear regression was performed around the inflection point using multiple linear regression analysis. The results revealed that social jetlag (82.0 [85.0] min) was experienced by 64.6% of the shift-working nurses. After controlling for confounding variables, the model with seven knots had the lowest accepted Akaike information criterion value, and there was a U-shaped relationship between shift-working nurses' BMI and social jetlag in this model; its inflection (lowest) point of 20.7 was considered the cut-off point. Segmented regression showed that for BMI < 20.7, BMI was significantly negative with standardized social jetlag; whereas with BMI > 20.7, BMI was significantly positive with standardized social jetlag. BMI has a U-shaped relationship with social jetlag, and attention should be paid to overweight or underweight shift-working nurses to detect early circadian rhythm disorder. Shift-working nurses with high social jetlag tended to have higher/lower BMI, which should be further investigated in the future, to minimize metabolic diseases among them.

Comparison of Ten Surrogate Insulin Resistance and Obesity Markers to Identify Metabolic Syndrome in Mexican Adults

Metabolic syndrome (MetS) is a group of clinical traits directly linked to type 2 diabetes mellitus and cardiovascular diseases, whose prevalence has been rising nationally and internationally. We aimed to evaluate ten known and novel surrogate markers of insulin resistance and obesity to identify MetS in Mexican adults. The present cross-sectional study analyzed 10575 participants from ENSANUT-2018. The diagnosis of MetS was based on the Adult Treatment Panel III (ATP III) criteria and International Diabetes Federation (IDF) criteria, stratified by sex and age group. According to ATP III, the best biomarker was the metabolic score for insulin resistance (METS-IR) in men aged 20-39 and 40-59 years and lipid accumulation product (LAP) in those aged ≥60 years. The best biomarker was LAP in women aged 20-39 and triglyceride-glucose index (TyG) in those aged 40-59 and ≥60 years. Using the IDF criteria, the best biomarker was LAP in men of all ages. TyG gave the best results in women of all ages. The best biomarker for diagnosis of MetS in Mexican adults depends on the criteria, including sex and age group. LAP and TyG are easy to obtain, inexpensive, and especially useful at the primary care level.

Comparing Human-Smartphone Interactions and Actigraphy Measurements for Circadian Rhythm Stability and Adiposity: Algorithm Development and Validation Study

BACKGROUND

This study aimed to investigate the relationships between adiposity and circadian rhythm and compare the measurement of circadian rhythm using both actigraphy and a smartphone app that tracks human-smartphone interactions.

OBJECTIVE

We hypothesized that the app-based measurement may provide more comprehensive information, including light-sensitive melatonin secretion and social rhythm, and have stronger correlations with adiposity indicators.

METHODS

We enrolled a total of 78 participants (mean age 41.5, SD 9.9 years; 46/78, 59% women) from both an obesity outpatient clinic and a workplace health promotion program. All participants (n=29 with obesity, n=16 overweight, and n=33 controls) were required to wear a wrist actigraphy device and install the Rhythm app for a minimum of 4 weeks, contributing to a total of 2182 person-days of data collection. The Rhythm app estimates sleep and circadian rhythm indicators by tracking human-smartphone interactions, which correspond to actigraphy. We examined the correlations between adiposity indices and sleep and circadian rhythm indicators, including sleep time, chronotype, and regularity of circadian rhythm, while controlling for physical activity level, age, and gender.

RESULTS

Sleep onset and wake time measurements did not differ significantly between the app and actigraphy; however, wake after sleep onset was longer (13.5, SD 19.5 minutes) with the app, resulting in a longer actigraphy-measured total sleep time (TST) of 20.2 (SD 66.7) minutes. The obesity group had a significantly longer TST with both methods. App-measured circadian rhythm indicators were significantly lower than their actigraphy-measured counterparts. The obesity group had significantly lower interdaily stability (IS) than the control group with both methods. The multivariable-adjusted model revealed a negative correlation between BMI and app-measured IS (P=.007). Body fat percentage (BF%) and visceral adipose tissue area (VAT) showed significant correlations with both app-measured IS and actigraphy-measured IS. The app-measured midpoint of sleep showed a positive correlation with both BF% and VAT. Actigraphy-measured TST exhibited a positive correlation with BMI, VAT, and BF%, while no significant correlation was found between app-measured TST and either BMI, VAT, or BF%.

CONCLUSIONS

Our findings suggest that IS is strongly correlated with various adiposity indicators. Further exploration of the role of circadian rhythm, particularly measured through human-smartphone interactions, in obesity prevention could be warranted.

Association between Sleep Duration, Social Jetlag, and the Metabolic Syndrome by Shift Works

Lifestyle factors, including sleep characteristics, have been implicated in the development of metabolic syndrome, particularly among shift workers. This study aimed to explore the relationship between shift work, sleep duration, social jetlag, and the risk of metabolic syndrome among U.S. workers and the moderating effect of sleep duration and social jetlag on this relationship. Data from the National Health and Nutrition Examination Survey (NHANES) in 2017-2020 March were analyzed. Poisson regression models were employed to examine associations. Among 4136 U.S. workers, 53.3% had metabolic syndrome, with a higher proportion of shift workers (63.8% vs. 56.7%, p = 0.001) and those sleeping less than 6 h or more than 9 h per week (22.3% vs. 19.1%, p = 0.044) in the affected group. Shift workers were initially found to have an increased risk of metabolic syndrome (Coef. = 0.03, 95% CI: 0.02, 0.16); however, this association was mitigated when accounting for the interaction with social jetlag. Specifically, 1 to <2 h of social jetlag interacted significantly, increasing metabolic risk (Coef. = 0.15, 95% CI: 0.09, 0.22), whereas 1 to <2 h alone showed a protective effect (Coef. = -0.11, 95% CI: -0.17, -0.06). These findings suggest that optimizing sleep schedules and addressing social jetlag may be crucial in mitigating metabolic syndrome risks among shift workers.

Eating Patterns, Chronotypes, and Their Relationship with Metabolic Health in the Early Postpartum Period in Women after Gestational Diabetes Mellitus

Observational studies have shown a relationship between eating patterns and chronotypes with metabolic health in the general population and in healthy pregnancies. Data are lacking in the postpartum period, which is characterized by an externally driven misalignment of sleep and food intake. We investigated the associations between eating patterns, chronotypes, and metabolic health in the early postpartum period in women who had gestational diabetes mellitus (GDM). We prospectively included 313 women who completed their 6-8 weeks postpartum visit between January 2021 and March 2023 at the Lausanne University Hospital. Women filled questionnaires on the timing of food intake, sleep (a shortened Pittsburgh Sleep Quality Questionnaire), and the chronotype (the Morningness-Eveningness Questionnaire) and underwent HbA1c and fasting plasma glucose measurements. After adjustments for weight, sleep quality, or breastfeeding, the later timing of the first and last food intake were associated with higher fasting plasma glucose and HbA1c levels 6-8 weeks postpartum (all p ≤ 0.046). A higher number of breakfasts per week and longer eating durations were associated with lower fasting plasma glucose levels (all p ≤ 0.028). The chronotype was not associated with metabolic health outcomes. Eating patterns, but not the chronotype, were associated with worsened metabolic health in the early postpartum period in women with previous GDM.

Circadian desynchrony and glucose metabolism

The circadian timing system controls glucose metabolism in a time-of-day dependent manner. In mammals, the circadian timing system consists of the main central clock in the bilateral suprachiasmatic nucleus (SCN) of the anterior hypothalamus and subordinate clocks in peripheral tissues. The oscillations produced by these different clocks with a period of approximately 24-h are generated by the transcriptional-translational feedback loops of a set of core clock genes. Glucose homeostasis is one of the daily rhythms controlled by this circadian timing system. The central pacemaker in the SCN controls glucose homeostasis through its neural projections to hypothalamic hubs that are in control of feeding behavior and energy metabolism. Using hormones such as adrenal glucocorticoids and melatonin and the autonomic nervous system, the SCN modulates critical processes such as glucose production and insulin sensitivity. Peripheral clocks in tissues, such as the liver, muscle, and adipose tissue serve to enhance and sustain these SCN signals. In the optimal situation all these clocks are synchronized and aligned with behavior and the environmental light/dark cycle. A negative impact on glucose metabolism becomes apparent when the internal timing system becomes disturbed, also known as circadian desynchrony or circadian misalignment. Circadian desynchrony may occur at several levels, as the mistiming of light exposure or sleep will especially affect the central clock, whereas mistiming of food intake or physical activity will especially involve the peripheral clocks. In this review, we will summarize the literature investigating the impact of circadian desynchrony on glucose metabolism and how it may result in the development of insulin resistance. In addition, we will discuss potential strategies aimed at reinstating circadian synchrony to improve insulin sensitivity and contribute to the prevention of type 2 diabetes.

Physical Activity Pattern of Adults With Metabolic Syndrome Risk Factors: Time-Series Cluster Analysis

Background

Physical activity plays a crucial role in maintaining a healthy lifestyle, and wrist-worn wearables, such as smartwatches and smart bands, have become popular tools for measuring activity levels in daily life. However, studies on physical activity using wearable devices have limitations; for example, these studies often rely on a single device model or use improper clustering methods to analyze the wearable data that are extracted from wearable devices.

Objective

This study aimed to identify methods suitable for analyzing wearable data and determining daily physical activity patterns. This study also explored the association between these physical activity patterns and health risk factors.

Methods

People aged >30 years who had metabolic syndrome risk factors and were using their own wrist-worn devices were included in this study. We collected personal health data through a web-based survey and measured physical activity levels using wrist-worn wearables over the course of 1 week. The Time-Series Anytime Density Peak (TADPole) clustering method, which is a novel time-series method proposed recently, was used to identify the physical activity patterns of study participants. Additionally, we defined physical activity pattern groups based on the similarity of physical activity patterns between weekdays and weekends. We used the χ2 or Fisher exact test for categorical variables and the 2-tailed t test for numerical variables to find significant differences between physical activity pattern groups. Logistic regression models were used to analyze the relationship between activity patterns and health risk factors.

Results

A total of 47 participants were included in the analysis, generating a total of 329 person-days of data. We identified 2 different types of physical activity patterns (early bird pattern and night owl pattern) for weekdays and weekends. The physical activity levels of early birds were less than that of night owls on both weekdays and weekends. Additionally, participants were categorized into stable and shifting groups based on the similarity of physical activity patterns between weekdays and weekends. The physical activity pattern groups showed significant differences depending on age (P=.004) and daily energy expenditure (P<.001 for weekdays; P=.003 for weekends). Logistic regression analysis revealed a significant association between older age (≥40 y) and shifting physical activity patterns (odds ratio 8.68, 95% CI 1.95-48.85; P=.007).

Conclusions

This study overcomes the limitations of previous studies by using various models of wrist-worn wearables and a novel time-series clustering method. Our findings suggested that age significantly influenced physical activity patterns. It also suggests a potential role of the TADPole clustering method in the analysis of large and multidimensional data, such as wearable data.

Chronotype and lipid metabolism in Arctic Sojourn Workers

This study relates answers to the Munich Chronotype Questionnaire (MCTQ) and Pittsburgh Sleep Quality Index (PSQI) from Arctic Sojourn Workers (ASW) of Yamburg Settlement, 68° Latitude North, 75° Longitude East (n = 180; mean age ± SD; range: 49.2 ± 7.8; 25-66 y; 45% women) to Arctic Sojourn Work Experience (ASWE), age and health status. Chronotype, Mid Sleep on Free Days sleep corrected (MSFsc) and sleep characteristics of ASW were compared to those of age-matched Tyumen Residents (TR, n = 270; mean age ± SD; range: 48.4 ± 8.4; 25-69 y; 48% women), 57° Latitude North, 65° Longitude East. ASW have earlier MSFsc than TR (70 min in men, p < 0.0001, and 45 min in women, p < 0.0001). Unlike TR, their MSFsc was not associated with age (r = 0.037; p = 0.627) and was linked to a larger Social Jet Lag (+21 min in men; p = 0.003, and +18 min in women; p = 0.003). These differences were not due to outdoor light exposure (OLE): OLE on work (OLEw) or free (OLEf) days was not significantly different between ASW and TR in men and was significantly less in ASW than in TR women (OLEw: -31 min; p < 0.001; OLEf: -24 min; p = 0.036). ASWE, but not age, was associated with compromised lipid metabolism in men. After accounting for multiple testing, when corrected for age and sex, higher triglycerides to high-density lipoprotein ratio, TG/HDL correlated with ASWE (r = 0.271, p < 0.05). In men, greater SJL was associated with lower HDL (r = -0.204; p = 0.043). Worse proxies of metabolic health were related to unfavorable components of the Pittsburgh Sleep Quality Index in ASW. Higher OLE on free days was associated with lower systolic (b = -0.210; p < 0.05) and diastolic (b = -0.240; p < 0.05) blood pressure.

Morning Chronotype Is Associated with Improved Adherence to Continuous Positive Airway Pressure among Individuals with Obstructive Sleep Apnea

Rationale: Poor adherence limits the effectiveness of continuous positive airway pressure (CPAP) therapy for obstructive sleep apnea (OSA). A better understanding of CPAP adherence is needed to develop novel strategies to improve it. Objectives: To determine if the chronotype (morning, evening, or intermediate) of patients with OSA is associated with differences in CPAP adherence. If such an association exists, determine the mechanisms underlying this association. Methods: We performed a secondary analysis of the APPLES (Apnea Positive Pressure Long-term Efficacy Study) clinical trial. We assessed chronotype using the Morningness-Eveningness Questionnaire (MEQ) among participants randomized to the CPAP arm with daily adherence data (n = 469). Evening (MEQ ⩽ 41), intermediate (41 < MEQ < 59), and morning type (MEQ ⩾ 59) categories were the exposures. We modeled daily CPAP use (hours per night) over a 6-month period, using a linear mixed model, adjusted for covariates (e.g., age, sex, marital status). To assess mechanisms of the association, we performed mediation analyses using sleep duration, weekend catch-up sleep, depression, and other factors. Results: Most participants were obese men with severe OSA (body mass index of 32.3 ± 7.3 kg/m2, 65% male, and apnea-hypopnea index 39.8 ± 24.6/h). Participants were 44% morning, 47% intermediate, and 8% evening chronotype. Participants with the morning chronotype reported the shortest sleep duration on weekends (7.3 vs. 7.6 and 7.9 h/night) compared with the intermediate and evening types. Participants with the morning chronotype exhibited a 40-min/night higher CPAP use (P = 0.001) than persons with the intermediate chronotype. This relationship was mildly attenuated (32.8 min/night; P = 0.011) after adjustment for covariates. None of the selected factors (e.g., sleep duration, weekend catch-up sleep) exhibited a significant mediation effect. Conclusions: Morning chronotype is associated with a clinically meaningful increase in CPAP adherence compared with other chronotypes. Mechanisms of this association require further study. Chronotype may be a novel predictor of CPAP adherence. Clinical trial registered with www.clinicaltrials.gov (NCT00051363).

Evaluating causal associations of chronotype with pregnancy and perinatal outcomes and its interactions with insomnia and sleep duration: a Mendelian randomization study

IMPORTANCE

Observational studies suggest that chronotype is associated with pregnancy and perinatal outcomes. Whether these associations are causal is unclear.

OBJECTIVE

To explore associations of a lifetime genetic predisposition to an evening preference chronotype with pregnancy and perinatal outcomes, and explore differences in associations of insomnia and sleep duration with those outcomes between chronotype.

DESIGN SETTING AND PARTICIPANTS

We conducted two-sample Mendelian randomization (MR) using 105 genetic variants reported in a genome-wide association study (N=248 100) to instrument for lifelong predisposition to evening-versus morning-preference chronotypes. We generated variant-outcome associations in European ancestry women from UK Biobank (UKB, N=176 897), Avon Longitudinal Study of Parents and Children (ALSPAC, N=6826), Born in Bradford (BiB, N=2940) and Norwegian Mother, Father and Child Cohort Study (MoBa, with linked data from the Medical Birth Registry of Norway (MBRN), N=57 430), and extracted equivalent associations from FinnGen (N=190 879). We used inverse variance weighted (IVW) as main analysis, with weighted median and MR-Egger as sensitivity analyses. We also conducted IVW analyses of insomnia and sleep duration on the outcomes stratified by genetically predicted chronotype.

EXPOSURES

Self-reported and genetically predicted chronotype, insomnia and sleep duration.

MAIN OUTCOMES AND MEASURES

Stillbirth, miscarriage, preterm birth, gestational diabetes, hypertensive disorders of pregnancy, perinatal depression, low birthweight and macrosomia.

RESULTS

In IVW and sensitivity analyses we did not find robust evidence of effects of chronotype on the outcomes. Insomnia was associated with a higher risk of preterm birth among evening preference women (odds ratio 1.61, 95% confidence interval: 1.17, 2.21), but not among morning preference women (odds ratio 0.87, 95% confidence interval: 0.64, 1.18), with an interaction P-value=0.01. There was no evidence of interactions between insomnia and chronotype on other outcomes, or between sleep duration and chronotype on any outcomes.

CONCLUSIONS AND RELEVANCE

This study raises the possibility of a higher risk of preterm birth among women with insomnia who also have an evening preference chronotype. Our findings warrant replications due to imprecision of the estimates.

Key points

Question: Does an evening preference chronotype adversely affect pregnancy and perinatal outcomes? Is there an interaction between chronotype and either insomnia or sleep duration in relation to those outcomes?Findings: There was no evidence that evening preference was associated with pregnancy or perinatal outcomes. Women with a genetically predicted insomnia had a higher risk of preterm birth, if they also had a genetically predicted preference for evening chronotype.Meaning: The suggestive interaction between insomnia and evening preference on preterm birth, if replicated, supports targeting insomnia prevention in women of reproductive age with an evening chronotype.

Evaluating the Relationship between Circadian Rhythms and Sleep, Metabolic and Cardiovascular Disorders: Current Clinical Evidence in Human Studies

Circadian rhythms are generated by the circadian clock, a self-sustained internal timing system that exhibits 24-h rhythms in the body. Many metabolic, cellular, behavioral and physiological processes are regulated by the circadian clock in coordination with environmental cues. The present study is a comprehensive review of the currently existing evidence concerning the relationship between circadian rhythms and sleep, metabolic, and cardiovascular disorders. We thoroughly searched the online databases PubMed, Scopus, and Web of Science to find the existing clinical studies from the last twenty-three years (2000-2023). Circadian misalignment was found to be associated with an increase in the risk of metabolic disorders, cardiovascular diseases, and obesity, as well as inadequate sleep quality. In this review article, all the included studies had a strength protocol design and all of them were conducted on humans. However, the most common limitations of them were the small sample size and the short time of the intervention. In conclusion, managing the factors that disrupt the optimal function of central and peripheral clocks can help to reduce the risk of metabolic and cardiovascular diseases, improving also sleep quality. Future studies should further explore the underlying mechanisms of the interconnections between circadian clocks and sleep, metabolic, and cardiovascular disorders. This may provide new opportunities for advance chronotherapy approach.

The relationship between chronotype and obesity: A systematic review

Referring to the hours during a day when a person's physical and cognitive functions are active, the chronotype indicates the differences in individual preferences in sleep timing and other behaviors. The fact that the evening chronotype has been associated with adverse health outcomes has raised the issue of relationship between chronotype and obesity. This study aims to synthesize the evidence regarding the relationship between chronotype and obesity. As part of the study, the PubMed, OVID-LWW, Scopus, Taylor & Francis, ScienceDirect, MEDLINE Complete, Cochrane Library and ULAKBIM databases were screened for the articles published between January 01, 2010 and December 31, 2020. The quality of each study was assessed independently by the two researchers using the "Quality Assessment Tool for Quantitative Studies." Upon evaluating the screening results, a total of seven studies, one of high quality and six of medium quality, were included in the systematic review. The rate of the minor allele (C) genes, which have been associated with obesity, and SIRT1-CLOCK genes, which have an additional effect in favor of resistance against weight loss, is higher in individuals of evening chronotype, and such individuals have been observed to have significantly higher resistance to weight loss. The evening chronotype individuals have been associated with a higher homeostasis model assessment (HOMA) value, higher plasma ghrelin levels, and a tendency toward a higher body mass index (BMI). The evening chronotypes have been reported to adhere less to a healthy diet and have more unhealthy behaviors and eating patterns. A diet adjusted to the chronotype has been seen to be more effective than conventional hypocaloric diet therapy in terms of anthropometric parameters. Most people who eat their main meals late are of evening chronotype, and such people have been determined to lose significantly less weight than those who eat early. It has been shown that bariatric surgery is less effective in weight loss in evening chronotype patients than in morning chronotype patients. The evening chronotypes are less successful in adapting to weight loss treatments and long-term weight control than the morning chronotypes.